The instant invention relates to improved methods and systems for analysis of dynamic electrocardiograms and other similar waves of biological origin with the purpose of facilitating improved diagnosis of pathological states in human and veterinary medicine. More particularly, the instant invention advantageously uses advances in sound wave technology to improve the recovery, preservation, enhancement and cost effective analysis of biological signals to aid research as well as medical and veterinary diagnosis.
Coronary heart disease is the main cause of death in many countries. About 50% of those affected do not reach the hospital due to poor recognition of the disease before a cataclysmic, often terminal event has occurred. The present invention facilitates improved recognition of myocardial ischemia in and out of the hospital by lay people with minimum training. Once the nature of the event is recognized, prompt treatment can then be obtained with a net effect in the decrease of morbidity and mortality and thereby providing substantial gains in life span and in quality of life.
Heretofore, visual analysis of the ambulatory electrocardiogram, in its original analog format, has been and remains unsurpassed and it is superior to any and all current computerized forms of analysis. Visual analysis is a very time consuming (hence costly) process, which required an operator with intimate knowledge of electrocardiography and cardiology. For this reason the use of visual analysis has been limited to academic research and it has not been possible to extend its benefit to patient care in the community. The instant invention overcomes this problem and enables identification of the abnormal patterns by any person with normal intelligence with a minimum (few hours) amount of training in the recognition of the discrete visual patterns which are repetitive between and within patients.
The instant invention, referred to herein as the Computerized Visual Analysis Technique or xe2x80x9cCVATxe2x80x9d, generally relates to the use of state-of-the-art electronics, computer hardware and software and forward looking signal analysis principles of technology for the evaluation of biological signals obtained from isolated cells, tissues, human and animal species to aid research and diagnosis of medical and veterinary disease states. CVAT can be used to process biologic signals such as, but not limited to: 1) the electrocardiogram in all it""s forms, and in particular, the continuous electrocardiographic signal such as that obtained with the Holter technique or during on-line, real time monitoring of a patient; 2) the electroencephalogram; 3) the myogram; 4) the phonocardiogram; and 5) Respiratory sound waves including their correlation with the electrocardiogram and encephalogram to diagnose sleep disorders in the hospital and in out of hospital settings.
CVAT remedies major limitations of the current Holter analysis paradigm which is useful only to detect gross arrhythmia on the 24-hr electrocardiogram (ECG). Current computerized analysis of the ambulatory ECG is done without due regards for protection of the integrity, fidelity, resolution or dynamic range of the analog signal recorded. The current methods are unable to reliably detect ambulatory ischemia or risk for potentially lethal arrhythmia. Such risks are not detectable in a cost-effective manner with prior art techniques. These shortcomings of the prior art have a significant impact on cardiovascular morbidity and mortality. CVAT remedies the failure of the current methodology by making full use of the valuable information encoded in the ambulatory electrocardiogram. By failing to disclose evidence of risks for catastrophic events, current Holter analysis lulls clinicians into the falsehood of absence of evidence misrepresented as evidence of absence of potentially lethal risks. Consecutive obsolete methodologic steps in current Holter analysis severely diminish the quantity and degrade the quality of the signal encoded in original Holter recording media.
Mass screening for patients silently at risk for potentially lethal cardiovascular events could save hundreds of thousands lives in the United States alone. Well done ambulatory ECG monitoring is the only method able to detect transient myocardial ischemia and spontaneously occurring electrical alternans. More than half of the myocardial infarcts and sudden cardiac deaths happen without any prior history of cardiac disease. The instant inventor has determined that these occult and lethal risks can be detected and lives saved if Holter analysis is done with all the resources made available by the fast advances constantly made in signal analysis and computer technology.
As many as 80 to 100% of the myocardial ischemic episodes in a patient can be asymptomatic or have uncharacteristic manifestations known as xe2x80x9canginal equivalentsxe2x80x9d by cardiologists but frequently undetected by non-cardiologists. Silent and or uncharacteristic ischemic events are common especially in females, diabetics, hypertensives, smokers, hypercholesterolemics, etc. Endothelial cell dysfunction and occult coronary heart disease are frequently hidden pathophysiologic causes of catastrophic or lethal cardiac events.
Silent ischemia, especially that which is not induced by physical stress, can be detected only by ambulatory ECG. However, today, the only reliable form of Holter analysis is visual scanning of the magnetic tape itself, not the xe2x80x9cover readingxe2x80x9d of the expunged and distorted digital file which misrepresents the original signal. Visual analysis by an expert electrocardiographer is a very time consuming method used only by highly motivated experts in research programs. Due to time and cost involved, visual analysis of the analog signal cannot be applied to clinical practice or mass screening of at risk population with known methods. To detect ischemia, special attention must be paid to microvolt range changes in the ECG, which are not preserved or duly analyzed by current Holter algorithms. There is a need in the art to develop an improved method of Holter analysis that can be made cost effective by not requiring highly sophisticated operator skills. In accordance with the invention, preservation of the signal integrity, dynamic range, fidelity and resolution in the time and voltage domains are of paramount importance for accurate diagnosis of electrocardiographic abnormalities. These considerations are literally of vital importance especially regarding the microvolt region of the ECG where the ventricular repolarization is encoded.
The current computerized methods of Holter analysis use communications engineering techniques and thoroughly obsolete computer hardware and software. Communications engineering paradigms and techniques are best limited to the evaluation of non-biological signals where reproducibility and repetition of waves and other phenomena are the norm. Biologic signals, such as the electrocardiogram, arise from complex biological entities where individuality, constant variation and irreproducibility are expected. A major drawback of engineering autocorrelation is that it is sensitive to waveform changes in the time domain (X-axes) and poorly sensitive to changes in the voltage domain (Y-axes). In current Holter analysis, autocorrelation is wrongly applied to a small sample of degraded biological signal with poor dynamic gain which magnifies the limitations of autocorrelation to recognize voltage changes. Non-biological techniques used to analyze biological data yield, at best, mediocre results, which become poor when analysis is done using a distorted, minuscule fraction of the original signal recorded.
The present invention remedies the deficiency of the current art by completely turning away from over reliance in engineering paradigms not applicable to biology and technology and methodology which has long become obsolete. Rather than using autocorrelational techniques, CVAT analyzes morphology, Avisual patterns and internal harmony in the time intervals. Since it""s discovery at the beginning of the century, electrocardiography remains a highly visual, pattern and morphology based discipline. Despite sophisticated efforts (such as neural network or fractal strategies) to advance computer science, humans still do better visual pattern recognition than computers. In CVAT, morphologic patterns are quickly and easily recognized by non sophisticated technicians. Expansion of abnormal, visually compressed, ECG patterns lead to precise identification of important, classical electrocardiographic signs that can not be identified by current Holter analysis. CVAT evaluates time intervals as reflection of harmony or disharmony within the recording; comparisons with the xe2x80x9cnormxe2x80x9d are done with caution. Current Holter computer analysis relies on quantification of duration and voltages in a digital file degraded in quantity and quality to compare these findings to idealized xe2x80x9cnormalxe2x80x9d values obtained with different and better equipment
There are two basic types of ambulatory ECG recording systems. The xe2x80x9cretrospectivexe2x80x9d system (commonly known as Holter recording) analyzes the collected data after completion of the signal recording phase. The xe2x80x9creal-timexe2x80x9d system analyzes data as it is being recorded. Retrospective systems record the ECG on magnetic tape (usually the cassette type) or flash cards to subsequently analyze the data. In either system, the recording is done through a plurality of input leads attached through electrodes to various points on the patient""s chest. To analyze the ECG, real-time systems generally include a microprocessor in conjunction with the electronic storage device. Both the real-time and the retrospective recording systems are designed to interface with a scanner through a magnetic tape reader or an electronic interface to download the collected information for analysis, editing, storage, and reporting.
To record sound, cassette decks use a magnetic tape speed of 55 mm per second across the recording head. For Holter recording the tape speed is reduced 50 to 100 times to speeds of 1.1 to 0.55 mm per second. Such drastic speed reduction is necessary to do 24 hours recordings without changing cassettes. Speed fluctuation in the 10% range is a signal acquisition problem; the best research efforts have dropped it to 3%, which is still too high for accurate quantitative ECG analysis. The time-base fluctuation is magnified when the low-speed recording is played back at very high speeds. The magnetic tape is orders of magnitude richer in signal quantity and quality than the very small digital file used for current forms of analysis. The norm today is to digitize the analog signal by playing back the cassette tapes at speeds as fast as 480 times real time; this is the beginning of major degradation of the analog ECG.
Cassette tape decks used for Holter processing are inexpensive, less than precise instruments. High-speed playback degrades fidelity by limiting frequency response. Inaccuracy and signal deterioration is also introduced by biasing and/or misalignment of the tape on the play back head during high-speed play back. Tape stretching due to repeated stopping and starting of the tape is another source of signal degradation. CVAT solves these problems, in part, by using the high quality decks to play back the tape once, in an uninterrupted manner, at a speed preferably lower than 37 times real time. The digital signal may, for example, then be copied from a hard drive and archived in a compact disc.
Independent channel enhancement of the dynamic range is an important step introduced by CVAT and not done in the current Holter art. The signal encoded in each channel of the magnetic tape is fed into a sound mixer for independent expansion of the dynamic range prior to digital encoding using the best possible or high quality sound card. In accordance with the invention, sampling of the analog signal is preferably done at rates of 44,100 to 96,000 Hz with 16-bits quantization, per sample, per channel. Higher sampling and quantization rates may also be used. The current Holter art samples, at best, at 8,000 Hz with 8-bits cards without preservation of the signal integrity or enhancement of dynamic range prior to analog to digital conversion.
Current Holter analysis is entirely dependent upon the extraction of an unselected fraction of the analog signal encoded in a 24-hour Holter tape. Current algorithms use elision and omission of vast amounts of the originally recorded ECG signal to achieve extreme, unnecessary and deleterious data compression. For instance, at the June 1999 Drug Information Association meeting, Mortara et al. announced, as a novel achievement, the launch of 24 hr 12 leads Holter that will be stored in 16 megabytes of a flash card (over 100,000 heart beats in 1.33 MB per lead per 24 hr). Obsolete clipping and distortion of the signal housed in novel media.
On the surface, the quest for radical compression strategies (xe2x80x9cdecimatingxe2x80x9d) would seem to be adequate in that it saves memory and greatly enhances the portability of Holter data. However, extreme digital compression gravely decreases the integrity, fidelity, resolution and most importantly the dynamic range of the stored electrocardiogram or any other signal. Furthermore, in the current art, Fast Fourier Transformation is used to artfully create xe2x80x9cimaginary pointsxe2x80x9d to replace discarded original data and xe2x80x9csmoothxe2x80x9d the now partially fictitious signal. Such creative approach is done after drastic lossy compression has irretrievably discarded more than 90% of the original signal with great loss of integrity, dynamic range, resolution and fidelity. The end product is the current art""s inability to detect ischemia, pacemaker malfunction, arrythmogenic risk or any condition other than gross ventricular arrhythmia.
Gross data clipping and xe2x80x9cimaginaryxe2x80x9d data points only partially explain the major limitations of today""s Holter analysis. The continuing use of vastly outmoded computer and signal processing technology impede the use of Dr. Norman Holter""s invention to it""s full diagnostic potential to save human lives. Data compression strategies used in current Holter analysis date back to the accidental creation of the Y2K problem. Obsolete and unnecessary compression strategies reduce 24-hours worth of analog Holter data down to a little more than a single megabyte digital file. When the algorithms for Holter analysis were created, extreme limitations in available memory existed. Thus, extreme data compression was needed. It is not accidental that the 1 megabyte and fraction file was perfectly portable in a single 3.5xe2x80x3 magnetic floppy disk and suitable for telephonic transmission with now grossly obsolete modems. The fact that Apple Computers, Inc. has altogether ceased to issue computers with 3.5xe2x80x3 magnetic floppy disk drives is an indication of how outmoded such a standard for data-volume has become. Thirty years ago, in the infancy of the computer industry, when silicon chips were as expensive as they were limited in their RAM or ROM capacity, data compression was a necessary evil. The Y2K problem was created by a generation of computer programmers who, squeezing every last bit of possibly available data space from the mainframes and PCs of the past, deemed it frivolous to reserve then-precious RAM or ROM memory for the two digits xe2x80x9819xe2x80x99 in any and all indications of the year. Now that computer memory is as cheap as it is truly vast in capacity, data compression is an undesirable tool mainly used by producers of entertainment and other non-essential computer applications, i.e. whenever loss of data is deemed acceptable for reasons of practicality and/or fast transmission over consumer-level internet connections.
Like all biologic signals, ECG, as audio data are remarkably hard to compress effectively. All compression routines are known to deteriorate dynamic range, signal quantity and quality. For 8-bit data, a Huffman encoding of the deltas between points has been used in current Holter analysis but deterioration of the signal is quite evident. For 16-bit data, companies like Sony and Philips are spending millions of dollars to develop proprietary schemes that as yet are not fully successful. If somehow, truly non-lossy audio compression would become able to compress 350 megabytes (the size of a CVAT 24 hr ECG file) of data and, even more importantly, preserve high fidelity, resolution and dynamic range intact within a single megabyte of memory, such a compression strategy would be almost a miraculous gift to the computer industry and technology in general. Although great strides of innovation are now being made in techniques of data compression, a 350:1 data compression ratio keeping the integrity of the signal is as yet impossible, nor is it necessary. The fundamental pitfalls of current Holter algorithms are the same than those which were silently at work in the creation of the Y2K bug: automated data compression algorithms which discard data deemed inessential to the projected application. To be of any value, pre-compression selection of data to be invisible, inaudible, illegible, or otherwise useless, is a must. The problem is that such pre-compression decision regarding ambulatory ECG signal is not and can not be made without rendering compressed Holter files useless except for detection of gross arrhythmia.
The much-hyped MPEG Layer 3 (or xe2x80x98MP3xe2x80x99) strategy of digital audio compression, for instance, uses a psychoacoustic algorithm to determine which sonic frequencies in a given audio recording remain ultimately audible to the ear of a listener. The data corresponding to all xe2x80x98irrelevantxe2x80x99 frequencies are then omitted from the resulting compressed sound files. Although the algorithm used in MP3 compression is quite advanced, the process still degrades the quality of the original signal in an invariably noticeable (almost xe2x80x98trademarkxe2x80x99) fashion. Such degradation, however, lies within an xe2x80x98acceptablexe2x80x99 window of loss for the consumer-oriented purposes of the technology, i.e. exchanging recordings of popular songs over the Internet. Boasting a powerful 12:1 compression ratio, MP3 is a fairly new compression strategy. Even newer, xe2x80x98betterxe2x80x99 strategies are being invented on almost a quarterly basis, but all of them, even the latest xe2x80x98fractalxe2x80x99 compression strategies, still ultimately boil down to the same compression paradigm: automation of the a priori decision to selectively preserve or omit certain types of data. Detection of microvolt and lower voltage changes in the ECG is relatively new in the electrophysiology lab and now brought to ambulatory ECG with the instant CVAT method. It is not yet known which voltage changes are unimportant and to be disposed with impunity.
One overriding fact remains clear: the application of any inherently omissive data compression strategies to a 24 hr ECG recording prior to any and all analysis of the totality of the signal is wrong. The only possible use of such indiscriminately selected file is detection of conditions expected to be apparent within the grossly compressed version of the ECG signal. For the current Holter analysis, that condition was and remains gross arrhythmic events. For a phenomenon as eponymously elusive as xe2x80x98silent ischemiaxe2x80x99, for instance, such a stark predetermination of what will and will not be detectable in an electrocardiogram is, literally, the most fatal omission of all. Detection of silent ischemia and risk of fatal arrhythmia is done in the microvolt region of the signal, the area that suffers the most from dynamic range and signal quality deterioration due to obsolete signal processing schemes. Current Holter analysis continuing reliance upon obsolete signal and data handling strategies limits access only to that portion of ECG data which was thought worth representing within a single megabyte of computer memory more than 10 years ago. Holter analysis remains a vastly under addressed technological obsolescence which is an obstacle for detection of risk for lethal events and in doing so puts lives directly at risk.
The numbers speak for themselves: Digital compression of 24 hours of recorded signal down to as low as a single megabyte unnecessarily omits about 99.6% of the ECG which can be easily retrieved from the average 24-hour magnetic Holter tape. It is like attempting to xe2x80x9creadxe2x80x9d a book while missing 99.6% of the words or xe2x80x9cwatchxe2x80x9d a film with 99.6% of the celluloid frames omitted. Diagnosis of potentially life threatening conditions can and should not be made based on such scanty and non-discriminatingly selected fraction of the ECG stored in the original recording media. Human life protection deserves better than that.
The instant CVAT process for Holter analysis utilizes a completely different method of xe2x80x9cdata compressionxe2x80x9d altogether, one which does not omit any portion or aspect of the originally recorded ECG Holter data. Instead of destructive fast play back of the tape and digital compression of the Holter data, CVAT improves the dynamic range electronically prior to slowly encoding the whole, unmodified analog signal using the highest possible sample rate and quantization. CVAT decodes the digital file into an optimum analog display which itself can be visually compressed, magnified at will and processed without suffering any loss, but rather being enhanced by various different processes which are made available by CVAT and its related software. In addition, the only limits containing further development and refinement of the CVAT process are those temporarily imposed by the ephemeral and upwardly spiraling limits of computer and signal analysis technology. The CVAT process remains an infinitely upgradeable, high-quality system which takes Holter analysis orders of magnitude beyond current techniques.
Referring now to FIG. 1, there is shown a exemplary Holter electrocardiogram. The P wave is the ECG representation of the atrial depolarization which cause its contraction. PQ is the segment between the P and the Q; it represents the delay of the electrical wave of depolarization at the atrioventricular node to allow the contraction of the atria and fill the ventricles before the latter depolarize and expel blood into the body. Ta (a microvolt shift in the PQ not present in this figure) is due to abnormal atrial repolarization caused by ischemia. The QRS is the ECG representation of ventricular depolarization which cause ventricular contraction. The ST segment represents the initial repolarization of the ventricles. The ascending limb of the T wave represents epicardial (outer surface of the ventricle) repolarization which changes into endocardial (inner surface of the ventricle) and mesocardial repolarization at the apex of the upright T wave. Ventricular repolarization is complete when the T wave returns to the isoelectric line. Several different morphologies of the T wave are associated with non-homogeneous repolarization, a sign of myocardial cell hypoxygenation and risk for lethal arrhythmia. TP is the isoelectric segment between the offset of the T and the onset of the P waves. TP must be considered as the isoelectric line when Ta is present. The second beat is a premature depolarization characterized by abnormal QRS and T morphology as well as greater voltage and duration than the normal beats.
Experts in non-ambulatory electrocardiography do visual analysis of the 12 lead ECG using 10X optical magnification for which special tracings are taken at two or four times the normal paper speed (i.e. 50 to 100 mm per second paper speed) with at least twice the electrical gain (i.e. 1 millivolt inscribing a 20 mm deflection). The tracings are done using good quality, well maintained and well-calibrated stationary electrocardiographs. The best examples of this art are in research done in Scandinavia. There is a pressing need to apply similar or better care to the processing and analysis of the ambulatory electrocardiogram.
Norman J. Holter Ph. D. created Holter technology using radio-transmitted electrocardiograms in the 1940""s. The method was used for diagnosis of arrhythmia. The first algorithms for computer assisted analysis were designed to detect and classify premature or aberrant beats for the diagnosis of arrhythmia. Attempts to automate detection of myocardial ischemia started in the early 1970""s. Systems to do Holter ECG processing and evaluation are well known as disclosed in U.S. Pat. Nos. 3,229,687; 4,006,737; 4,098,267; 4,183,354; 4,211,238; 4,316,249; 4,333,475; 4,336,810; 4,633,881; 4,667,682; 4,883,065; 4,989,610; 5,205,295; 5,398,183 and 5,433,209.
Automated evaluation of ST segment shifts was attempted with only minor modifications of the basic signal processing and algorithms used for arrhythmia detection. The ischemia algorithm compares the voltage at one 8-bits point in the ST segment (located 60 to 100 milliseconds beyond the J pointxe2x80x94the junction of the QRS and the ST segment) to the voltage at another 8-bits point on the PQ taken as the isoelectric line. Correction for presence of Ta (atrial ischemia) is unheard off in the current art, since it is unable to visualize this subtle but important change. Hence, in the current art, the ST segment (a line and, as such, defined by at least two points) is represented by a single point. The analytic paradigm and totally obsolete limitations in computer technology imposed this major source of false negative reports.
Identification of the isoelectric line in the ECG is of paramount importance for detection of atrial and ventricular ischemia as well as for evaluation of the QT segment and T wave changes indicative of abnormal repolarization and arrhythmogenic risk.
Current Holter algorithms can not detect ECG signs of abnormal repolarization in a reliable and reproducible manner. Ischemic events, represented by ECG signs of abnormal repolarization and depolarization, are usually unexpected and transient. Abnormal repolarization is visualized as microvolt shifts in the PQ segments (Ta) if atrial or ST segment and T wave if ventricular. In the current Holter art, Ta is undetected and mistakenly chosen as the isoelectric point. This false isoelectric point and spill over of the Ta negative voltage into the ST segment are common pitfalls that introduce error in ischemia detection by current algorithms. Down shift of the ST by Ta depends on the degree of atrial ischemia, the heart rate, atrioventricular conduction velocity, etc. CVAT can easily recognize such problems and use the TP segment, instead of the PQ, as the isoelectric reference line. The TP segment is inscribed from the end of the T to the beginning of the P waves in two consecutive beats. CVAT can also identify the influence of Ta into the ST segment and discriminate false positive up sloping ST depression (starting from a depressed J point) from up sloping ST depression likely to be due to ventricular ischemia.
The prior art taught by conventional Holter monitoring systems cannot retrieve, store, display or analyze high fidelity signals in the microvolt or microsecond range. Fast magnetic tape play back done without optimizing the dynamic range, scanty sampling, poor quantization and extreme data compression deteriorate and diminish the signal. However, computer memory (1.2 Megabytes) and processing time are saved and telephonic transmission of a scanty, low fidelity, low resolution, low dynamic range signals file is facilitated. Fast Fourier Transformation and other algorithmic manipulations are used to automate processes, reduce operator time and level of skill, speed analysis and decrease cost. All the above contribute to the poor diagnostic performance of current Holter technology for conditions other than gross arrhythmia.
The present invention (CVAT) preferably uses: the best possible electronic technology for integral signal recovery with preservation and enhancement of the dynamic range, fidelity, time and voltage resolution of biologic waves encoded in any recording media; the best possible computer and signal analysis technology to digitize the analog biologic signals for storage, further enhancement, and archival preservation of the signal; and the best possible electronic, computer and signal analysis technology for the recovery, display and evaluation of the signals for basic research, medical and veterinary diagnosis.
Ambulatory electrocardiography done according to the Holter technique was used for the initial testing of the CVAT method and system. CVAT can be used in research, clinical practice and mass screening as an aid to diagnose cardiovascular conditions which include, but are not limited to: 1) Myocardial ischemia in all it""s forms; and 2) Repolarization (including but not limited to QT prolongation and electrical alternans) and depolarization heterogeneity as signs of increased cardiovascular risk.
The instant CVAT invention enables extension of Holter monitoring analysis to the detection and interpretation of ECG signals at and beyond the microvolt and micro second range. These minute changes encode important diagnostic and prognostic information not discernible from current Holter techniques or other forms of electrocardiographic analysis. Conventional Holter monitoring and ECG systems cannot detect, preserve or recover signals at or beyond the microvolt or microsecond range. Exception is made of techniques limited to the electrophysiology laboratory not applicable to mass screening or daily clinical practice outside of specialized centers.
The CVAT invention provides a method for biologic signal analysis by trained but not medically skilled technicians. Cost effective processing is aided by a variety of well identified morphologic patterns obtained by visual compression, in the X (time) axes of the played back signal. The visually compressed patterns are highly suggestive or patognomonic of important electrocardiographic changes which are confirmed by examination of the expanded ECG tracing.
The purpose of algorithms in current use is to provide an ECG evaluating system, as automated as possible, which scans the tape as fast as possible with minimal or no operator interaction. Undue reliance is placed on a physician over reading of very small depictions of low fidelity greatly deteriorated ECG tracings recovered from the digital file. Unless the over reader reviews the whole analog signal encoded in the original recording media (in addition to editing the computer findings), ischemic and other events missed by the computer can not be detected. This is the most common and potentially fatal shortcoming of the current Holter art. Visual examination of the analog recording is exceptional; it is done only in very few research centers and not by Holter analysis services that support clinical practice or research in general.
Current computerized Holter analysis algorithms use heartbeat superimposition and template-matching schemes to recognize departures from normal. Which beats, in a pool of about 100,000 in 24 hours, are the norm for a patient? This is a basic problem which has to be dealt with even when neural networks, used in research only, select beats to xe2x80x9ctrainxe2x80x9d the computer to recognize xe2x80x9cnormalxe2x80x9d beats. After digital conversion, each heartbeat becomes a series of digital values representing XY points of the waveform at various intervals. In current Holter analysis the number of digital points per heartbeat is, at best, 33 or lower if the heart rate goes above 60 beats per minute. The computer does beat matching to evaluate the difference between values at various points of the waveform and to compare such values with corresponding points of templates. A match is defined as any sum of the absolute value of each of the differences within a preset range. The closest match is called the matching template. If no template matches, the operator must classify. The degraded signal preserved by the current art allows only the grossest matching which cannot go beyond identification of largely aberrant beats. In addition, current algorithms include software to analyze the series of waveforms according to a nondeterministic logic state analysis. This analysis permits the systems to indicate when waveforms correspond to ventricular ectopy (VE), bigeminy, VE pair, and ventricular tachycardia, only.
A standard waveform has a P wave, a QRS complex and a T wave. As it is well known in the prior art, the QRS complex is generally identified by its major peak, usually the R wave. The T wave is then identified as the first peak after the R wave. A T wave template is used to process the wave quickly and inadvertent recognition of a T wave as an R wave is minimized but still exists. The T wave template is a classification that the operator may apply when asked to classify the xe2x80x98beatxe2x80x99. Thereafter, any peak that matches the T wave template is totally ignored, as though no peak had been found at the position. If the operator incorrectly classifies a T peak that is or looks like a real beat, that type of beat will be ignored. Therefore, the method is used as a last resort, when setting the other parameters does not help, which can occur with patients who have peaked T waves. Peaked T waves are a common early manifestation of ischemia. Whenever the ST segment shifts up or down due to myocardial ischemia, the T morphology is usually abnormal and not amenable to template classification. While templates work well for arrhythmia, over reliance in abnormal beat classification using predetermined templates is a reason for the poor performance of computer automated Holter analysis in the diagnosis of conditions other than arrhythmia.
The template matching method is probably good enough for ventricular and other gross forms of arrhythmia, which manifest themselves by millivolt range changes in the QRS. However superimposition of fast played back, scantily sampled, mercilessly compressed, filtered, smoothed and/or Fast Fourier Transformed beats cannot be trusted, since it processes a signal different from that originally encoded in the magnetic tape. Template detection may be convenient, but applied to a digital file which lacks integrity, dynamic range, fidelity and resolution, it cannot be sensitive or specific nor can it detect abnormalities in microvolt regions such as the PQ, ST segments or the P and T waves.
The sophisticated cardiology community is aware of the current Holter analysis shortcomings; hence, this method is not routinely used as an aid in the diagnosis of highly lethal cardiovascular risks.
The following passage is taken verbatim (bolding added) from U.S. Pat. No. 5,398,183 issued on Dec. 10, 1990. This algorithm is widely used in patient care and research and further demonstrates the disadvantages of current Holter processing techniques.
xe2x80x9cAs another feature of the invention, a full disclosure file representing the entire series of waveforms on the tape is generated. The file comprises compressed data of limited resolution and limited sampling rates. The original data is reduced in resolution by skipping, averaging, or otherwise xe2x80x9cdecimatingxe2x80x9d samples, only using samples at a rate near 33 samples per second with reference to the patient data. (This is an equivalent rate of 33 samplesisec of the data generated when the patient was originally monitored by the analog Holter monitor. Of course, the data reading rate off the tape is much faster.) In this system 100, this is accomplished by averaging 4 samples, or by picking one out of every fourth sample. The data is scaled in amplitude (and limited) so that the total excursion is 32 levels. The 32 levels are sufficient resolution to plot on a laser plotter at 200 dots/inch, producing a 0.15xe2x80x3 tall waveform. The sample frequency (referenced to patient) is sufficient to see all R-peaks of normal beats by position, and to display the waveforms of ventricular beats sufficiently clearly to be identified. The data is then further compressed by using a series of coding steps. First the data is converted to differential coding. (This is a version of DPCM, xe2x80x98Differential Pulse Code Modulationxe2x80x99 in the telecommunications industry). Each sample has the previous sample subtracted from it (as the example in FIG. 7 shows). This is a simple, and computationally efficient means to produce codes which consist mostly of the smaller integers near 0. In fact, the output will often have runs of 0s, or +1s, 0, and xe2x88x921s. Less frequently the differences will be larger numbers (6 to 31), mostly near the R peaks. The differential output is limited to the range xe2x88x9231 to +31. The data is then encoded further using a variation of xe2x80x98Huffmanxe2x80x99 coding, or other codes which use few bits for symbols which occur frequently, and more bits for symbols which occur infrequently. (The symbols to be coded are the 63 integers in the range xe2x88x9231 to 31). This may be combined with run length coding, which is the coding of a repeated sequence of the same symbol with a code representing the sequence in fewer bits than repetitions of the code representing the symbol singly. The result of this coding is to bring the number of bits to represent a data point down to around 2 to 3 bits. This typically allows 24 hours of data to occupy less than 1 megabyte, where a byte is 8 bits. (3/8 byte/ sample * 33 sample/sec * 60 sec/min * 60 min/hr * 24 hr/tape=1.07 Megabyte/tape). This allows the full disclosure to typically be stored on a single IBM PC compatible 1.2 Megabyte diskette, or transferred by telephone in 10-20 minutes using the new 9600 Baud Modems.xe2x80x9d
xe2x80x9cTaking every third sample provides a limited sampling rate and scaled differential coding provides limited resolution. Further compression, such as run length and Huffman coding, may then be used so that the full disclosure file can be even further significantly reduced in size. The differential values 0, +1, xe2x88x921, +2, xe2x88x922 may be seen to occur more frequently than the larger values of 6 to 31 and xe2x88x926 to xe2x88x9231. If the smaller integer values are represented by codes using two or three bits, then the size of the file can be further reduced. FIG. 8 is an example of a part of a limited resolution, full disclosure file recreated from differentially encoded, compressed data. The circled areas indicate ventricular ectopy and supra-ventricular ectopy which is clearly recognized even though this portion of the file was created from compressed data.xe2x80x9d
The best resolution to be expected with the algorithm described in this patent are 33 points in the X axes and 32 points in the Y axes to inscribe one heart beat if the heart rate is 60 beats per minute. If the heart rate goes to 120 per minute there will be, at best, 16 points to describe the whole cycle length.
After the xe2x80x9cdecimating compressionxe2x80x9d it is only benign to say that the algorithm driven file will have poor resolution and fidelity. A 24-hour Holter recording is housed in 1.2 Megabytes, and yet a 3-minute song, reproduced with any decent degree of fidelity, takes about 30 to 40 times the memory currently allocated to a 24 hours Holter recording. This is a grave problem that needs immediate redress. In contrast, CVAT encodes the same 24 hours Holter recording in about 350 megabytes. The CVAT file improves the dynamic range and preserves the integrity, fidelity and resolution of the signal recorded. It is not surprising that the quality of the ECG recovered from current Holter analysis algorithms is too poor to identify anything but arrhythmia with some degree of certainty. The substantial difference made by CVAT""s preservation and enhancement of the signal has been demonstrated in a retrospective study done comparing CVAT with the best current algorithm analysis. The results of this study are provided below.
The passage below, taken from the U.S. Pat. No. 4,989,610 issued on Feb. 5, 1991, illustrates problems in another crucial point of current Holter analysis (bolding added).
xe2x80x9cThe first step in this portion of the program reads the six items contained in the beat time log (BTL) for a particular beat 1220 (see FIG. 55). The data in the BTL is 16 bits wide. It includes the bin number (to be assigned by the binning operation (BIN#)), a 32-bit number indicating the time of occurrence of the beat in terms of {fraction (1/120)} second samples of time (BTH and BTL), a TEMP location for temporary storage of data, a FLAG word, an 8-bit ST measurement, and an 8-bit ST-slope measurement.xe2x80x9d
xe2x80x9cThe data representing one channel of the present beat consists of thirty-two samples. The tenth sample corresponds to the location of the R-wave, as determined by the beat detection software. Nine samples preceding the location of the R-wave and twenty-two samples immediately following the location of the R-wave constitute the remainder of the samples.xe2x80x9d
xe2x80x9cThen, the DSP chip 300 performs the Fast Fourier Transform (FFT) on the thirty-two samples of the channel 1data, producing sixteen pairs of real and imaginary data.xe2x80x9d
xe2x80x9cThe pattern describing the members of this first bin are the twelve points in the complex plane 1236, with each point being associated with either channel 1 or channel 2 and with one of the six frequencies. The six pairs of numbers that describe the pattern for the second and following beats are compared, according to their channel and frequency, with the groups of points that defines the bins already in existence. If the twelve points characterizing the morphology of a beat whose bin is being determined are sufficiently close, on a point-by-point basis, to the twelve points of an already existing bin, that beat may be associated with that bin. If the twelve points describing the morphology of a present beat do not come sufficiently close to all twelve points describing all already-existing bin, a new bin is defined. The twelve points defining the new bin are the twelve points characterizing the morphology of the most recent beat. The twelve points describing a beat need not match precisely with the twelve beats defining a bin for the beat to possibly be placed in the bin. The twelve points describing the morphology of the beat are sufficiently close to the twelve points defining the bin if each of the twelve points falls within windows centered on the points defining the bin.xe2x80x9d
The passage teaches that 32 samples represent a heartbeat in each channel and that these samples are subjected to Fast Fourier Transform to generate xe2x80x9csixteen pairs of real and imaginary dataxe2x80x9d. These sixteen pairs of xe2x80x9creal and imaginaryxe2x80x9d data cannot be expected to fully describe the complex morphology of each heartbeat. With this algorithm, all the microvolt nuances will certainly be irretrievably lost. These brief passages provide strong reasons to render this algorithm useless for anything but arrhythmia detection.
The current automated systems for Holter analysis retrieve only a small portion of the analog signal. Excessively fast play back speed of the tape, low sampling and quantization rates, xe2x80x9clossyxe2x80x9d and drastic data compression, Fast Fourier Transform to interpolate imaginary data, filtering, smoothing, etc. are done to accommodate the need for very small data files suitable for telephonic transmission and automated analysis. The price paid is extremely poor ECG data unsuitable for recognition of ischemic and other dire electrocardiographic signs with any degree of certainty.
Myocardial ischemia is the result of oxygen debit in the heart muscle and conduction system due to increased demand or decreased supply of oxygen which cannot be fulfilled because of: 1) organic, fixed, coronary artery stenosis such as that seen in patients with atherosclerotic plaques in the luminal wall of their coronary arteries; 2) functional, episodic, often unpredictable constriction of normal or atherosclerotic coronary arteries; or 3) clot formation over an atherosclerotic plaque.
Although spasm was historically suspected to be a cause of coronary occlusion, from the 1940""s to the 1960""s the common wisdom was that atherosclerotic arteries were unable to constrict. In the 70""s experts in the field demonstrated that atherosclerotic plaques are mostly eccentric with a small free arterial wall (opposite to the atheromatous plaque) likely to cause total occlusion when minor spasm of such small free wall occurs. When coronary artery spasm happens, gaps between the endothelial cells happen, collagen protrusion induces platelet aggregation and in-situ clot formation. Thrombosis can also lead to partial or total occlusion following the arterial spastic episode.
Fixed, organic, atherosclerotic arteries can be readily identified. The conventional 12-lead electrocardiogram can disclose patognomonic signs of permanent (not episodic) ischemia of the heart. The 12-lead electrocardiogram is not expected or designed to detect transient and unpredictable episodes of myocardial ischemia or arrhythmia since it depicts only 3 of the 100,000 or more heart beats we have in 24 hours. For detection of sporadic arrhythmic or ischemic events, usually triggered by diverse stressful stimuli of daily living, properly done Holter recording is the only available method, electrocardiographic or otherwise.
Permanent (not episodic) myocardial ischemia due to fixed coronary artery occlusion can be detected by several methods other than Holter. Electrocardiography and or echocardiography done during standardized exercise challenge can detect ischemia and/or arrhythmia induced by physical stress. Other, more invasive methods, such as drug induced stress testing (the pharmacologic induction of increased cardiac oxygen demand by administration of drugs which elevate the heart rate), nuclear radiology or cardiac catheterization, are designed to detect fixed coronary artery occlusion.
All methods available today, other than the Holter technique, are unable to detect myocardial ischemia due to transient spastic and/or thrombotic causes of decreased coronary blood flow. Coronary artery spasm frequently happens without preceding elevation of the heart rate and/or blood pressure and is commonly triggered by neurohormonal, emotional and/or environmental (e.g. exposure to cold, second hand smoking etc) factors, not inducible in controlled cardiovascular laboratory circumstances. Hence, this grave condition escapes detection unless Holter recordings are done under the fleeting and often difficult to identify forms of daily life stress that induces the attacks in a given patient. The current Holter recording equipment has enough fidelity to detect these episodes. The limiting factor is the current computerized Holter analysis that is unsuitable for detection of anything but gross arrhythmia. The current art suffers from false negative findings which have dire consequences for patients considered healthy when they are not. Today, the only reliable method to analyze Holter recordings for ischemia is the direct visual inspection of the analog tape by a competent electrocardiographist. Such visual Holter analysis is time consuming and hence, done only in few research efforts and not cost effective or applicable to daily clinical practice or mass screening.
Computerized Holter analysis was designed for the detection of arrhythmia, and has remained essentially unchanged. Arrhythmia induces gross changes in the time and voltage domains of the recording. Algorithms to detect arrhythmia rely on large, millivolt range. lschemia-induced abnormalities are in the microvolt range and are unlikely to stand the decimating affects of current algorithms devoted to minimize file size. Norman J. Holter, Ph. D. originally designed his valuable method and technology (U.S. Pat. No. 3,229,687. January 1966. Holter et al.) for the study of heart rate and rhythm. The minor changes introduced by computer algorithms are not sufficient for reliable detection of ischemia or risk for potentially lethal arrhythmia.
In cardiovascular diagnosis, it is important to monitor the level of the ST segment of the heart beat signal since the amplitude and direction of the shift correlate well with the oxygen balance in the patient""s heart. A heart receiving insufficient oxygen experiences predictable anomalies in the ST segment called xe2x80x9cST Depressionxe2x80x9d or xe2x80x9cST Elevationxe2x80x9d. The names relate to the directional shift (negative or positive microvolts in reference to the isoelectric line) and shape of the ST segment of the ECG waveform during periods of insufficient heart oxygenation. The magnitude and morphologic changes of the T wave are additional indicators of ischemia which the current algorithms are unable to detect. The CVAT method makes full use of morphologic changes in all portions of the ECG to aid in the diagnosis of ischemia and arrhythmia risk.
The normal ST segment is located at the isoelectric level which usually aligns with the PQ or TP segments. PQ segment shift is frequently due to artifacts or ischemia of the atria (Ta). The normal condition is generally referred to as the xe2x80x9cisoelectric alignmentxe2x80x9d of the ST segment. ST segment shifts, measured in microvolts, above or below the isoelectric line are a reflection of abnormal myocardial repolarization due to inadequate LA oxygenation of the heart. Ischemia not felt by the patient is generally referred to as xe2x80x9csilent ischemiaxe2x80x9d, while ischemia which is painful is called xe2x80x9canginaxe2x80x9d. All or most ischemic events may be silent. Frequently 80 to 90% of the ischemic episodes can be asymptomatic or have uncharacteristic manifestations known as angina equivalents. However, silent or symptomatic, ischemia can equally induce arrhythmia, myocardial infarction or sudden death. It is suspected that silent ischemia is the underlying problem in the 50% of patients who have myocardial infarctions or die suddenly without having had any premonitory symptoms or signs.
It is very important to identify the isoelectric line and the level of the ST segment in the patient""s normal heartbeats in order to be able to properly identify departures from normality. U.S. Pat. No. 5,433,209 issued on Jul. 18, 1995 includes the following passage (not direct quotes and bolding not in the original document):
For each ECG signal channel, the QRS peak location is approximated from the point at which a beat is detected over a beat detection threshold. Then, the ST algorithm backs up 10 samples from the peak of the QRS complex to approximately land on the PR interval of the beat wave form. Next, a region of xe2x80x9cminimum activityxe2x80x9d is located and the baseline offset, identified as xe2x80x9cBase Corr (i)xe2x80x9d, is found. The xe2x80x9cminimum activityxe2x80x9d region is found by finding the smaller of the two 3-point absolute value derivatives in a 5 sample window on the PR interval. The baseline offset is taken for the sample which is located 30 samples forward of the QRS peak which is thereafter identified as the ST segment. The baseline offset at the region of xe2x80x9cminimum activityxe2x80x9d is subtracted from the sample value at this point and the difference, measured in millimeters, is taken to be the ST level. Each time a ST level is calculated, a last eight beats ST level average is also calculated. Each ST level average during the minute is compared to the last eight beat minimum and maximum ST level average to find the minimum and the maximum eight beat average for the minute. Hourly and monitoring period minimum and maximum ST levels are also determined in the above fashion. ST level sums are also maintained in the minute summaries, hour summaries and the end of monitoring period summary, with the corresponding normal beat counts. The minute ST level averages are calculated by dividing the minute ST level sum by the normal beat counts during the minute. The hour ST level averages are also calculated in a similar fashion. The minimum, maximum, and average ST levels are each stored as a signed byte of information. Each value is used along with the gain set for each channel and the analog to digital range set for each channel in order to calculate the ST depression or elevation value. Since, the ST averages all require extensive computations, the computational load is spread over several periodic interrupt cycles. Minute ST level averages are monitored over the entire monitoring period to determine an ST xe2x80x9cepisodexe2x80x9d. An xe2x80x9cepisodexe2x80x9d is detected if the minute ST level average in any channel is at least less than xe2x88x921.0 mm and is sustained at this depressed level for more than a minute. ST episodes of less than xe2x88x921.0 mm, xe2x88x922.0 mm, and xe2x88x923.0 mm and their duration time in minutes are recorded.
All these intensive computational niceties are done on a digital file known to be incomplete and with major fidelity, resolution and dynamic range deficiencies. Hence, it is not surprising that current algorithms miss 9 out of 10 patients whose ischemia can be identified with visual analysis.
In the current practice of cardiology, the goal of therapy for patients with coronary artery disease is being upgraded from simply controlling anginal pain to a more rational and forward looking reduction or elimination of silent and symptomatic ischemic episodes. Any form of ischemia, symptomatic or not, short or long can kill or induce myocardial infarction. Properly done, the Holter method is the only way to detect silent or atypically symptomatic ischemia and has to play an increasingly important role in the management of this serious condition. To play that important role in the detection and monitoring of ischemia the current Holter art risk of false negative analysis must be eliminated. Biologic signal analysis can and should make a quantum leap using, electronic technology, hardware and software developments achieved in the last decade.
Sudden cardiac death (SCD) claims over 350,000 lives annually in the United States; 50% of which had no premonitory symptoms or signs. SCD usually follows an abrupt disruption of heart rhythm primarily due to ventricular fibrillation. Fibrillation occurs when transient triggers impinge upon an electrically unstable heart causing normally organized electrical activity to become disorganized and chaotic. Complete cardiac dysfunction results and may end in sudden death. An episode of poor oxygenation of the heart (myocardial ischemia) is probably the most frequent cause of ventricular fibrillation and death.
A major, and as yet elusive, objective of preventive cardiology is to detect patients at risk for catastrophic arrhythmic cardiac events, including sudden cardiac death. Methodology used to identify subjects at risk must be improved. Electrical alternans is the electrocardiographic manifestation of heterogeneous myocardial repolarization and depolarization. Electrical alternans and ischemia are prominent indicators of risk factors for major catastrophic or lethal cardiac events. Gradual microvolt changes are seen in the ST segment and the T wave and are not as abrupt as the onset of abnormal QRS. Microvolt signals are easily obliterated by poor dynamic range, xe2x80x9cdecimatingxe2x80x9d compression algorithms, creation of xe2x80x9cimaginaryxe2x80x9d points, etc used by algorithms in the quest for automation and trans-telephonic transmission of minimized Holter files.
Cost effective, non-invasive, techniques for mass screening and identification of individuals at risk for catastrophic cardiac events that affect close to 2 million persons per year in the US alone are needed. Diagnostic technology must be constantly revised to make full use of the ever improving developments in electronics as well as computer hardware and software. Prompt risk detection, will lead to immediate confirmatory diagnosis, interventional cardiac catheterization, coronary artery by-pass, pharmacologic management, etc., thereby allowing the saving of hundreds of thousand of lives in the world. There is need to develop an improved Holter analysis that can be cost effective in time and level of operator skill and still precise enough to avoid potentially catastrophic false negative reports.
Advent of Holter analysis as a reliable method to detect ischemia and risk for severe arrhythmia will also facilitate targeted new drug development by providing valid objective therapeutic end points, instead of unreliable surrogate end-points. Cutting age technology has to be used to preserve the fidelity, dynamic range, time and voltage resolution of the recorded signal, a step of paramount importance for the accurate diagnosis of electrocardiographic abnormalities in the microvolt region. Holter analysis obsolescence is the medical counterpart of the Y2K problem with the difference that it""s cost in mortality and morbidity is orders of magnitude greater than the Y2K can ever be. This problem is greatly reduced, if not completely solved, by the teachings of the present invention.
The use of the instant invention to process analog electrocardiographic signals makes it possible to evaluate every single beat of the ambulatory electrocardiogram by compacting the signal in a manner that will disclose sui-generis visual patterns which correspond to and readily identify classic, discrete anomalies of the electrocardiogram, described by experts in the field as part of pathologic conditions compromising the cardiovascular system. The understanding of these patterns make it possible to identify the abnormal elements of the electrocardiogram.
The immediate value to mankind provided by the instant invention is that it makes possible identification in a non-invasive and cost-effective manner, patients who have silent myocardial ischemia and hence are at high risk for myocardial infarction, sudden death and other catastrophic events. About one half of patients with myocardial infarction, sudden death, lethal arrhythmias, etc. are patients who have no history of coronary heart disease and are probably carriers of silent myocardial ischemia, which triggers the terminal events leading to the patient""s demise. The instant invention enables timely discovery of this covert condition and enables timely anti-ischemic therapy which will result in the saving of millions of lives as well as a decrease in hospital use, disability and improvement of the quality of life of those affected by silent ischemia a potentially lethal condition.
As explained in detail above, instead of visual analysis, computer programs implementing mathematic algorithms are presently routinely used to perform analysis of electrocardiograms in an attempt to detect abnormalities therein. Such computer programs have had only limited success in diagnosing pathological conditions which compromise a patient""s cardiovascular system. Due to their cost-effectiveness, however, such mathematical techniques are widely used today. As a result, many patients have had pathological conditions go undetected.
Thus, a need exists for improved methods and systems which enable improved detection of pathological conditions during analysis of the electrocardiogram and other waves of biological origin.
The instant invention advantageously uses algorithms and computer programs created for the purpose of editing, manipulating and/or analyzing sonic and/or electromagnetic waves, such as music processing programs.
A primary object of the instant invention is to increase the accuracy and decrease the cost of biologic signal analysis for use in mass screening, clinical practice and research.
The instant invention, referred to herein as the Computerized Visual Analysis Technique or xe2x80x9cCVATxe2x80x9d, generally relates to the use of up-to-date signal processing technology with state-of-the-art electronic and computer technology for the evaluation of biologic signals obtained from isolated cells, tissues, human and animal species to aid basic research and diagnosis of medical and veterinary disease states. CVAT can be used to process biologic signals such as, but not limited to:
The electrocardiogram in all it""s forms, and in particular, the continues electrocardiographic signal such as that obtained with the Holter technique or during on-line, real time monitoring of a patient.
The electroencephalogram
The myogram
The phonocardiogram
Respiratory sound waves including their correlation with the electrocardiogram and encephalogram to diagnose sleep disorders in the hospital and in out of hospital settings, etc will be evaluated.
The invention also enables the generation of a report of the evaluation and the triggering of alarms in the real time monitoring mode.
CVAT is different from current forms of biological signal analysis in that it preserves the integrity of the analog signal, enhances dynamic range, the fidelity and resolution of the original signal obtained. All these features lead to better interpretation of the signal using compressed visual patterns, which, in turn, leads to quick and easy identification of abnormalities suggestive of pathologic states. CVAT is based on the application to biological signal analysis of advances made in the software, hardware and electronic technology used to process and analyze sound waves. This is a major departure from current obsolete ways to digitize analog signals, which include the use of extreme lossy digital compression, Fast Fourier Transformation and other mathematical and autocorrelational engineering based algorithms which markedly deteriorate the quantity and quality of the signal to be evaluated.
A main application of the present invention is to improve the analysis of the Holter electrocardiogram. The invention departs from the current Holter ambulatory electrocardiogram analysis in that it replaces auto-correlational communications engineering techniques and quantification-dependent analysis of the electrocardiogram done with obsolete computer technology which eliminates most of the original signal and distorts the fidelity, resolution and dynamic range of the small fraction kept in the digital file for algorithm driven analysis.
Instead, CVAT relies on morphologic and pattern evaluation signal analysis complemented with quantification when necessary. The totality of the signal originally recorded is preserved with protection and enhancement of dynamic range, resolution and fidelity of the signal.
The following features represent the main aspects of the instant CVAT invention, and together enable the invention to provide optimal processing and analysis of biologic waves:
Prior to analog to digital conversion, each lead of the ECG or other biologic signal undergoes electronic enhancement of the dynamic range;
Analog to digital conversion is done with the best possible equipment and the slowest possible play back speed of the originally recorded signal;
An optimum quality sound card is used for analog to digital conversion using the highest possible sample (preferably 44,100 Hz per second per channel or higher) and quantization (preferably 16-bits per sample per channel or higher) rates;
Digital sound processing software and techniques are used for the processing and analysis of biological signals. The inventor has determined that one suitable sound processing software is SOUND FORGE, which is designed for processing digital audio. Other similar software programs (such as, but not limited to seismographic and geologic software) used for wave analysis may also be used in accordance with the present invention. Such software allows various steps to be performed to enhance the signal (without introducing distortion) in the voltage and time domains and enhances pattern visualization and other forms of analysis;
The invention preferably used file formats originally created for sound wave applications (such as, but not limited to .wav and other similar file extensions) to process the biological signals;
Computer sound cards (such as but not limited to the Montego Bay card) are used to code and decode the analog biologic signal;
Visual compression of the analog signal is used to display the signal with high fidelity, resolution and dynamic range to identify visual patterns used as indicators of abnormalities which can be confirmed by expanding the signal;
Use of visual pattern libraries to train technicians with low level skills to facilitate the cost effective use of CVAT for mass screening, clinical practice and research;
Use of time interval measurements in the biologic signal to asses internal functional harmony as a reflection of normality or pathology. Such time intervals can be measured with a precision at or below 10,000th of a millisecond and will be even more reliable when better recording techniques are introduced. Normal standards applicable to the method used will be created to replace normal values extrapolated from data obtained with better equipment and in different circumstances. Extrapolated quantitative standards lack precision; and
Use of screen capture software (such as, but not limited to, Paint Shop Pro) to document the findings of the analysis and to transfer the images to graphic processing programs (such as but not limited to Adobe PhotoShop). This software is used for magnification and preparation of the report of the analyses.
In accordance with another aspect of the invention, internal harmony in the duration of different intervals of the electrocardiogram is advantageously used, and relies more on relative than on absolute duration. Internal harmony is done to evaluate repolarization of the myocardial cell according to the relationship between:
Cycle length duration measured as the J-J interval
Total duration of ventricular repolarization measured as J-Te and related to cycle length as (J-Te/J-J) X100
Transmural repolarization time measured as Tp-e related to the total duration of ventricular repolarization as (Tp-e/J-Te)xc3x97100
In accordance with another aspect of the invention, the method is used to detect microvolt and lesser changes in the ST segment, T wave, etc., as an indication of myocardial ischemia or electrical alternans or non-homogeneous repolarization and/or depolarization in ambulatory, cost effective conditions.
In accordance with another aspect of the invention, the method is used for evaluation of microvolt and lesser changes in the PQ interval shown as Ta changes suggestive of atrial ischemia.
In accordance with another aspect of the invention, morphologic patterns are used to detect transient or intermittent myocardial ischemia when other forms of Holter analysis are useless in evaluating recordings with artifacts, bundle branch block, ventricular hypertrophy, previous myocardial infarctions, etc.
In accordance with another aspect of the invention, morphologic patterns are used to detect intermittent atrioventricular or intraventricular blocks potentially caused by cardiac pathology such as, but not limited to, ischemia.
In accordance with another aspect of the invention, the method is used to detect traditionally minor (less than 1 mm shift in the current art) considered xe2x80x9cnon-specificxe2x80x9d ST segment shifts as sign of important ischemia risk. This is done by correlating the ST shift to the QRS as percent of the preponderant wave of the QRS normalized to its maximum potential using the CVAT software described herein.
In accordance with another aspect of the invention, the method is used for on-line monitoring of the electrocardiogram and other biologic signals.
In accordance with another aspect of the invention, the method is used to analyze simultaneously obtained upper airway breath sounds and the electrocardiogram to detect sleep apnea at home or elsewhere.